Cultural Studies QA Lead

Role overview

This remote contractor position is for a Cultural Studies Quality Assurance Lead focused on humanities-related AI training work. You will be responsible for keeping output consistent, accurate, and aligned with project standards across art history, visual culture, cultural studies, and broader humanities tasks.

The role is hourly and remote, and it supports a fast-growing AI data services company that provides training data to leading AI companies and foundation model teams. Your work will help improve AI systems by making sure humanities content is historically grounded, culturally aware, visually informed, and clearly written.

There is no active project to begin with right away. If you are a strong fit, you will be contacted first when suitable opportunities open up, and you may also gain access to future projects through the expert network.

What you will do

You will review AI-generated content and the work of trainers and QA contributors, checking it against detailed project rubrics and quality expectations. Your reviews will cover accuracy, interpretation, terminology, context, formatting, and sensitivity to cultural representation.

• Monitor quality by reviewing samples, identifying problems, and giving clear written feedback.
• Assess art history and cultural studies outputs for factual accuracy, interpretive depth, visual-analysis quality, and adherence to guidelines.
• Point out recurring issues and escalate serious or repeated problems when needed.
• Communicate guideline updates, workflow changes, and quality expectations to trainers and QA contributors.
• Answer questions about attribution, periodization, visual reading, cultural context, ethics, and rubric interpretation.
• Reach out to inactive contributors, encourage re-engagement, and track follow-ups.
• Maintain internal documentation such as style guides, FAQs, trackers, examples, honeypots, calibration tasks, and onboarding material.
• Run or support onboarding and training sessions for new trainers and QAs.
• Promote consistent use of review standards across the team as projects change.
• Flag stereotypes, Eurocentric framing, unsupported claims, decontextualized statements, and other bias or ethics concerns.
• Help improve processes and build scalable QA systems for humanities-focused AI training work.

Requirements

• A bachelor’s, master’s, or doctoral degree in Art History, Cultural Studies, Visual Culture, Museum Studies, Humanities, Fine Arts, Comparative Literature, Media Studies, Anthropology, History, or a closely related discipline.
• Strong English communication skills for guideline reading, team coordination, and precise written feedback.
• At least 3 years of experience in art historical research, cultural analysis, museum or curatorial work, teaching, academic writing, visual analysis, editing, cultural criticism, or a similar humanities-related workflow.
• Solid understanding of art history methods, visual analysis, iconography, style, periodization, patronage, medium and materials, museum ethics, cultural theory, representation, and historical context.
• Ability to judge content against detailed rubrics and detect issues such as misattribution, weak analysis, incorrect periodization, outdated terminology, stereotyping, unsupported interpretation, and context gaps.
• Preferred familiarity with areas such as ancient, medieval, Renaissance, modern, and contemporary art; non-Western art histories; photography; film and media; visual culture; postcolonial theory; gender studies; museum studies; or heritage studies.
• Previous experience leading or supporting remote researchers, writers, reviewers, educators, curators, annotators, or QA teams is strongly preferred.
• Comfort using collaboration and tracking tools such as Discord, Google Sheets, Google Docs, dashboards, trackers, and project management platforms.
• Strong organization and attention to detail, with the ability to keep documentation and review resources updated.
• Experience with AI training, data annotation, LLM evaluation, humanities QA, cultural sensitivity review, image review, or rubric-based evaluation is a strong advantage.

Additional information

This is a contract role based remotely. The selection process includes an AI interview, a domain-specific task, and a recruiter interview.

Although the role is linked to a remote team, the location listed for the position is Singapore.

The work is described as hourly, but no exact pay rate was provided.

Note: There is currently no immediate project attached to this opportunity; suitable candidates may be contacted later when relevant work becomes available.

Company focus: The employer is an AI data services company working on training data for large AI organizations and foundation model labs.